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Assessing Aortic Stenosis using Sample Entropy of the Phonocardiographic Signal in Dogs
Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Health Sciences.
Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Health Sciences.
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2008 (English)In: IEEE Transactions on Biomedical Engineering, ISSN 0018-9294, E-ISSN 1558-2531, Vol. 55, no 8, 2107-2109 p.Article in journal (Refereed) Published
Abstract [en]

In aortic valve stenosis (AS), heart murmurs arise as an effect of turbulent blood flow distal to the obstructed valves. With increasing AS severity, the flow becomes more unstable, and the ensuing murmur becomes more complex. We hypothesize that these hemodynamic flow changes can be quantified based on the complexity of the phonocardiographic (PCG) signal. In this study, sample entropy (SampEn) was investigated as a measure of complexity using a dog model. Twenty-seven boxer dogs with various degrees of AS were examined with Doppler echocardiography, and the peak aortic flow velocity (Vmax) was used as a reference of AS severity. SampEn correlated to Vmax with R = 0.70 using logarithmic regression. In a separate analysis, significant differences were found between physiologic murmurs and murmurs caused by AS (p < 0.05), and the area under a receiver operating characteristic curve was calculated to 0.96. Comparison with previously presented PCG measures for AS assessment showed improved performance when using SampEn, especially for differentiation between physiological murmurs and murmurs caused by mild AS. Studies in patients will be needed to properly assess the technique in humans.

Place, publisher, year, edition, pages
2008. Vol. 55, no 8, 2107-2109 p.
Keyword
Aortic stenosis (AS), bioacoustics, heart sound, murmur, sample entropy (SampEn)
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:liu:diva-13042DOI: 10.1109/TBME.2008.923767OAI: oai:DiVA.org:liu-13042DiVA: diva2:17715
Available from: 2008-03-20 Created: 2008-03-20 Last updated: 2017-12-13
In thesis
1. Nonlinear phonocardiographic Signal Processing
Open this publication in new window or tab >>Nonlinear phonocardiographic Signal Processing
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The aim of this thesis work has been to develop signal analysis methods for a computerized cardiac auscultation system, the intelligent stethoscope. In particular, the work focuses on classification and interpretation of features derived from the phonocardiographic (PCG) signal by using advanced signal processing techniques.

The PCG signal is traditionally analyzed and characterized by morphological properties in the time domain, by spectral properties in the frequency domain or by nonstationary properties in a joint time-frequency domain. The main contribution of this thesis has been to introduce nonlinear analysis techniques based on dynamical systems theory to extract more information from the PCG signal. Especially, Takens' delay embedding theorem has been used to reconstruct the underlying system's state space based on the measured PCG signal. This processing step provides a geometrical interpretation of the dynamics of the signal, whose structure can be utilized for both system characterization and classification as well as for signal processing tasks such as detection and prediction. In this thesis, the PCG signal's structure in state space has been exploited in several applications. Change detection based on recurrence time statistics was used in combination with nonlinear prediction to remove obscuring heart sounds from lung sound recordings in healthy test subjects. Sample entropy and mutual information were used to assess the severity of aortic stenosis (AS) as well as mitral insufficiency (MI) in dogs. A large number of, partly nonlinear, features was extracted and used for distinguishing innocent murmurs from murmurs caused by AS or MI in patients with probable valve disease. Finally, novel work related to very accurate localization of the first heart sound by means of ECG-gated ensemble averaging was conducted. In general, the presented nonlinear processing techniques have shown considerably improved results in comparison with other PCG based techniques.

In modern health care, auscultation has found its main role in primary or in home health care, when deciding if special care and more extensive examinations are required. Making a decision based on auscultation is however difficult, why a simple tool able to screen and assess murmurs would be both time- and cost-saving while relieving many patients from needless anxiety. In the emerging field of telemedicine and home care, an intelligent stethoscope with decision support abilities would be of great value.

Place, publisher, year, edition, pages
Institutionen för medicinsk teknik, 2008. 213 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1168
Keyword
Signal analysis methods, computerized cardiac auscultation system, phonocardiographic (PCG) signal, mitral insufficiency (MI), time- and cost-saving
National Category
Medical Laboratory and Measurements Technologies
Identifiers
urn:nbn:se:liu:diva-11302 (URN)978-91-7393-947-8 (ISBN)
Public defence
2008-04-25, Elsa Brändströmsalen, Universitetssjukhuset, Linköping, 09:00 (English)
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Available from: 2008-03-20 Created: 2008-03-20 Last updated: 2009-04-21

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Ahlström, ChristerHult, PeterAsk, Per

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